Trends, patterns, and maternal characteristics of opioid prescribing during pregnancy in a large population-based cohort study.

BACKGROUND: Opioid use during pregnancy has been associated with adverse maternal and infant health outcomes. Prescription drug monitoring programs (PDMP) provide a population-based source of prescription data. We linked statewide PDMP and birth certificate data in Tennessee (TN) to determine patterns of prescription opioid and benzodiazepine use during pregnancy. METHODS: We constructed a cohort of 311,217 live singleton births from 2013 to 2016 with prescription history from 90 days before pregnancy to birth. Descriptive statistics were used to describe opioid prescription patterns during pregnancy overall, by maternal characteristics and by year. Multivariable logistic regression models estimated adjusted odds ratios and 95% confidence intervals for factors associated with prescription use. RESULTS: The prevalence of prescription use during pregnancy was 14.1% for opioid analgesics, 1.6% buprenorphine for medication-assisted treatment, and 2.6% for benzodiazepines. The prevalence of opioid analgesic use decreased from 16.6% (2013) to 11.8% (2016) (ptrend< 0.001). About 25% used for > 7 and 9.7% for > 30 days' supply. The most common types were hydrocodone (9.3%), codeine (3.4%), and oxycodone (2.9%). In adjusted models, lower education, lower income, pre-pregnancy obesity and smoking during pregnancy were associated with increased odds of any opioid and opioid analgesic use. CONCLUSION(S): Despite the encouraging trend of decreasing use of prescription opioid analgesics, the overall prevalence remained close to 12% with many women using for long durations. Use was associated with lower socioeconomic status, obesity, and prenatal smoking. Findings highlight the need for maternal education and resources, and provider support for implementation of evidence-based care.

Characteristics of fatal opioid overdoses with stimulant involvement in Tennessee: A descriptive study using 2018 State Unintentional Drug Overdose Reporting System Data.

PURPOSE: Opioid overdose deaths involving stimulants are on the rise. Demographic characteristics for these deaths to be used in prevention efforts have not been established. METHODS: We conducted a statewide retrospective study to evaluate the characteristics of fatal opioid overdoses with stimulant involvement using 2018 Tennessee State Unintentional Drug Overdose Reporting System data. Data sources included death certificates, autopsy reports, toxicology, and prescription drug monitoring program data. Frequencies were generated to compare demographics, circumstances, opioid history, death scene information, bystander intervention, and toxicology between fatal opioid overdoses with and without stimulant involvement. RESULTS: A total of 1183 SUDORS opioid overdose deaths occurred in Tennessee in 2018 of which 434 (36.7%) involved a stimulant. Fatal opioid overdoses involving stimulants had higher frequencies of illicit drugs on toxicology specifically marijuana, fentanyl, and heroin compared to fatal opioid overdoses without stimulants. Fatal opioid overdoses involving stimulants had higher frequencies of scene indications of injection drug use compared to fatal opioid overdoses without stimulant involvement. CONCLUSIONS: Fatal overdoses are shifting from mainly opioid to multidrug involvement and over one-third include use of stimulants. This analysis can help public health practitioners understand the circumstances around fatal opioid overdoses involving stimulants to inform tailored prevention strategies.

Using statewide death certificate data to understand trends and characteristics of polydrug overdose deaths in Tennessee, 2013-2017.

PURPOSE: Population-based data on trends and characteristics on polydrug overdoses are critically needed to help understand the changing drug epidemic in the United States, and to identify risk patterns and targets for overdose prevention for prescription and illicit opioid deaths. We conducted a statewide study in Tennessee to evaluate characteristics and trends of polydrug overdose deaths during 2013-2017. METHODS: We identified polydrug overdose deaths using ICD-10 codes and literal cause-of-death text in the death statistical files. We evaluated trends, contributing drugs, and demographic characteristics of overdoses (n = 2567 single-drug and n = 4683 polydrug deaths). Average annual percent change estimates (AAPCs) with associated 95% CIs were estimated using Poisson regression. RESULTS: Polydrug overdoses increased annually, with higher AAPC for polydrug compared with single-drug overdoses (AAPC: 13.6%, 95% CI: 10.6%-16.7% and 5.2%, 95% CI: 2.9%-7.5%, respectively). The highest increases in polydrug overdoses were observed in males (AAPC: 15.4%, non-Hispanic blacks (AAPC: 33.3%), and decedents aged 18-34 years (AAPC: 21.3%). CONCLUSIONS: All drug and opioid polydrug deaths increased during 2013-2017, with the highest increases seen in males, blacks, and younger age groups. Over 80% of illicit opioid overdoses involved more than one drug, highlighting the need to go beyond opioids to prevent overdoses.

Record Linkage Approaches Using Prescription Drug Monitoring Program and Mortality Data for Public Health Analyses and Epidemiologic Studies.

BACKGROUND: The use of Prescription Drug Monitoring Program (PDMP) data has greatly increased in recent years as these data have accumulated as part of the response to the opioid epidemic in the United States. We evaluated the accuracy of record linkage approaches using the Controlled Substance Monitoring Database (Tennessee's [TN] PDMP, 2012-2016) and mortality data on all drug overdose decedents in Tennessee (2013-2016). METHODS: We compared total, missed, and false positive (FP) matches (with manual verification of all FPs) across approaches that included a variety of data cleaning and matching methods (probabilistic/fuzzy vs. deterministic) for patient and death linkages, and prescription history. We evaluated the influence of linkage approaches on key prescription measures used in public health analyses. We evaluated characteristics (e.g., age, education, sex) of missed matches and incorrect matches to consider potential bias. RESULTS: The most accurate probabilistic/fuzzy matching approach identified 4,714 overdose deaths (vs. the deterministic approach, n = 4,572), with a low FP linkage error (<1%) and high correct match proportion (95% vs. 92% and ~90% for probabilistic approaches not using comprehensive data cleaning). Estimation of all prescription measures improved (vs. deterministic approach). For example, frequency (%) of decedents filling an oxycodone prescription in the last 60 days (n = 1,371 [32%] vs. n = 1,443 [33%]). Missed overdose decedents were more likely to be younger, male, nonwhite, and of higher education. CONCLUSION: Implications of study findings include underreporting, prescribing and outcome misclassification, and reduced generalizability to population risk groups, information of importance to epidemiologists and researchers using PDMP data.